The Pedagogical Potential of Artificial Intelligence Programs in the Reproduction of Cultural and Historical Elements in Students’ Works

The article aims to study the potential of artificial intelligence programs in reproducing cultural and historical elements in students' works, depicting the cultural heritage of the East and Arab states. The study used empirical methods such as the experiment, survey, qualitative and quantitative analysis. The author’s model of project-oriented learning, which includes digital art techniques with the use of generative artificial intelligence technologies, was developed and tested. The possibilities of generative artificial intelligence services were tested within the educational experiment. The examples of digital artistic work of students resulting from interaction with generative artificial intelligence tools were presented. Results of the survey of teachers on the influence of the integration of artificial intelligence services in achieving pedagogical goals demonstrated the importance of these themes. Integration of artificial intelligence in the training of future artists and art teachers facilitates deeper understanding of art and its context (91%). It also contributes to the integration of theory and practice (87%) and the development of emotional bonds with art (86%). Special attention should be given to the development of critical artistic thinking (83%) and creativity (81%). The main limitation of this study is its descriptive-analytical nature, which requires a deeper analysis using both quantitative and qualitative methods. Further study prospects include the development of the models of evaluation of the influence of project-oriented learning integration on students’ development. Special attention shall be given to digital art techniques with the use of generative artificial intelligence technologies. These studies shall be oriented on exploring the influence on the development of critical and artistic thinking of students. Received: 29 November 2024 / Accepted: 15 March 2025 / Published: 08 May 2025